CU-8698jzjj3: flake8 fixes

Author: Tom Searle

medcat-v1/medcat/utils/ner/deid.py

@@ -190,7 +190,7 @@ def _get_reason_not_deid(cls, cat: CAT) -> str:
         return ""
 
 
-def match_rules(rules: List[Tuple[str, str]], texts: List[str], cat: CAT):
+def match_rules(rules: List[Tuple[str, str]], texts: List[str], cat: CAT) -> List[List[Dict]]:
     """Match a set of rules - pat / cui combos as post processing labels.
 
     Uses a cat DeID model for pretty name mapping.
@@ -210,6 +210,9 @@ def match_rules(rules: List[Tuple[str, str]], texts: List[str], cat: CAT):
             'My phone number is 1234567890',
         ]
         >>> matches = match_rules(rules, texts, cat)
+
+    Returns:
+        List[List[Dict]]: List of lists of predictions from `match_rules`
     """
     # Iterate through each text and pattern combination
     rule_matches_per_text = []
@@ -235,7 +238,7 @@ def match_rules(rules: List[Tuple[str, str]], texts: List[str], cat: CAT):
 
 def merge_preds(model_preds_by_text: List[List[Dict]],
                 rule_matches_per_text: List[List[Dict]],
-                accept_preds: bool = True):
+                accept_preds: bool = True) -> List[List[Dict]]:
     """Merge predictions from rule based and deID model predictions.
 
     Args:
@@ -267,6 +270,9 @@ def merge_preds(model_preds_by_text: List[List[Dict]],
             ]
         ]
         >>> merged_preds = merge_preds(model_preds_by_text, rule_matches_by_text)
+
+    Returns:
+        List[List[Dict]]: List of lists of predictions from `merge_preds`
     """
     all_preds = []
     if accept_preds:

medcat-v1/medcat/utils/ner/metrics.py

@@ -22,6 +22,13 @@ def metrics(p, return_df=False, plus_recall=0, tokenizer=None, dataset=None, mer
         return_df: Whether to return a DataFrame of metrics.
         plus_recall: The recall to add to the model's predictions.
         tokenizer: The tokenizer used to tokenize the texts.
+        dataset: The dataset used to train the model.
+        merged_negative: The negative labels to merge.
+        padding_label: The padding label.
+        csize: The size of the context window.
+        subword_label: The subword label.
+        verbose: Whether to print the metrics.
+
     """
     """TODO: This could be done better, for sure. But it works."""  # noqa
     predictions = np.array(p.predictions)